How to improve employee productivity (5 sources)

Every row is a verbatim sentence read from the named source's own page through our fetch service on the date shown, hash-pinned to the stored read (the sha of the page's visible text; the raw page is mirrored to R2).

3 of the 18 named sources that could be read published a usable figure; 15 published none and are recorded as not published, never filled in; 0 could not be read (blocked, dead or unreachable) and count nowhere.

The headline figures (median, minimum, maximum, quartiles) are over ONE figure per source for each breakdown it prices, in % (a source's median where its page yielded several accepted sentences for one breakdown), so a page that gives figures for several breakdowns gives one for each and N counts 5 figures, never sentences; 40 candidate sentence(s) were refused by a reviewer with the reason recorded.

The fuller derivation this dataset is chartered to grow into (not yet what the figures above are; they are each source's own published figure as read): one row per country per industry per period: output per hour worked at its published level and growth, joined across the national offices that each publish only their own country, with the OECD and Conference Board frames used to place a country in the distribution.

The figures nobody publishes are the JOINED ones: the gap between an industry's output per hour and the same industry in the best-performing country, the industry ranking inside a country, the spread between the best and worst region of one country (ONS publishes ITL regions, BLS publishes states, nobody puts them side by side), and the changed-since on every release date.

40 candidate sentences on these pages were refused by a reviewer; each refusal and its reason is recorded in the review ledger.